Today’s organizations are looking for better ways to pull the information they need from massive volumes of data available to them. Big data system administrators store, manage and transfer large sets of data, making them amenable to analysis. Data analytics is the practice of examining the raw data to identify patterns and draw conclusions. Business intelligence involves the collection and organization of information to report on business activities, often pulling data from those very sets.

Along with the surge in big data interest comes a growing number of certifications to recognize the necessary skills in working with enormous data sets. The target audience is IT professionals with a background in analytics, data mining, business intelligence or data management, along with a knack for and interest in mathematics and statistics. Big data engineers are in reasonably high demand and usually command salaries of $101,000 or more, where data scientists average about $128,500 in salary.

We took a detailed look at certifications from INFORMS, Microsoft, MongoDB, Oracle and SAS. Check out the results from our informal search of various job boards to see which certifications employers really want. However, these results are a snapshot from a specific day, time and geography, so they may not reflect real job demands in your locality when you search for yourself.

Job board search results (in alphabetical order, by certification)

*Certified Analytics Professional

CAP: Certified Analytics Professional

INFORMS is a membership-based association aimed at practitioners, researchers and instructors in analytics, as well as operations research and management sciences. The association reports about 12,500 members from nearly 90 countries, most of whom participate in various educational and networking opportunities via their INFORMS membership.

The organization also sponsors the vendor-neutral Certified Analytics Professional (CAP) certification. CAP focuses on seven domains of the analytics process:

• Business problem framing
• Analytics problem framing
• Data
• Methodology selection
• Model building
• Deployment
• Model lifecycle management

Candidates must meet rigorous education and experience requirements, obtain confirmation from a supervisor (current or former) of acceptable soft skills, agree to a code of ethics, and pass one computer-based exam.

This credential must be renewed every three years by earning 30 professional development units (PDUs). INFORMS also requires a $100 annual maintenance fee beginning in the fourth year after certification.

CAP facts and figures

MCSE: Data Management and Analytics

Microsoft is part of the big data mix with its MCSE: Data Management and Analytics certification, which leans heavily toward SQL Server 2016 and emphasizes cloud environments and reporting. This credential replaces the Microsoft Certified Solutions Expert (MCSE): Business Intelligence, which retired on March 31, 2017.

The MCSE: Data Management and Analytics requires candidates to earn an MCSA certification and then pass an elective exam. The MCSA certifications to choose from are MCSA: SQL Server 2012/2014; MCSA: SQL 2016 Database Administration; MCSA: SQL 2016 Database Development; MCSA: SQL 2016 BI Development; MCSA: Machine Learning; MCSA: BI Reporting; and MCSA: Data Engineering with Azure. There are 12 MCSE elective exams, which focus on a variety of cloud, big data analytics and BI topics, with machine learning now added to the MCSA certifications.

To maintain this certification, you must pass an additional elective test each year. Doing so adds an entry to your transcript that indicates your commitment to staying current on technologies and expanding your skill set.

MCSE: Data Management and Analytics facts and figures

Number of exams

*Exam to be retired on June 30, 2019. Replacement test not yet released but should be available prior to that date.

MongoDB NoSQL certifications

MongoDB is both an open-source, NoSQL document-oriented database and the name of the company providing that technology. Because of its document-oriented NoSQL model, MongoDB is well suited for managing large amounts of loosely structured data, as is so often the case in big data projects.

MongoDB was deemed a leader in Forrester Wave: Big Data NoSQL, Q3 2016, and Gartner selected MongoDB as a challenger in its 2016 Magic Quadrant for Operational Database Management Systems. The database ranks fifth in overall database engine popularity as of March 2019.

The MongoDB NoSQL certification program recognizes developers and operations professionals who can create and run applications on MongoDB. The program offers two associate-level credentials: MongoDB Certified DBA and MongoDB Certified Developer. The company plans to eventually roll out higher-level certifications. The current exams are based on MongoDB V4.0.

MongoDB offers private, instructor-led classroom training as well as free online video training through MongoDB University. Each online course typically runs for 3-7 weeks and features video lectures, quizzes, weekly assignments, and a final test or project. Students may use the forums to interact and address each other’s questions; instructors and teaching assistants monitor forums and jump in when needed.

For database professionals interested in venturing into big data projects and NoSQL databases, the MongoDB certification is certainly a worthwhile goal.

MongoDB NoSQL certification facts and figures

Oracle Business Intelligence certification

Oracle has one of the largest certification programs in the world, and it has granted more than 1 million Oracle and Sun certifications.

Oracle offers its Business Intelligence (BI) certifications across several applications and platforms, such as Business Intelligence Applications 7 for CRM, Business Intelligence Applications 7 for ERP, and Business Intelligence Foundation 11g. To narrow down the field, we focused on the Oracle Business Intelligence Foundation Suite 11g Certified Implementation Specialist credential.

Candidates for this certification are intermediate-level professionals (architects, analysts, developers and administrators) who work with Oracle Business Intelligence Suite solutions, performing tasks such as installing, building, querying, configuring, and managing the platform and BI dashboards.

Although anyone can attempt the exam, the certification is designed for members of the Oracle Partner Network who sell and deploy the technology.

New exams and training courses based on Oracle BI 12c are also becoming available as those courses and exams are released to the public.

Oracle Business Intelligence certification facts and figures

SAS Certified Data Scientist

SAS is a multibillion-dollar global corporation that specializes in business analytics software and services. The company’s well-honed certification program offers nine credentials across programming, information and data management, advanced analytics, and business intelligence.

Three noteworthy SAS certifications are the SAS Certified Data Scientist, SAS Certified Statistical Business Analyst Using SAS 9: Regression and Modeling, Business Intelligence Content Developer for SAS 9, and SAS Certified Big Data Professional Using SAS 9. We concentrated on the SAS Certified Data Scientist Using SAS 9.

Candidates for the Data Scientist certification should have in-depth knowledge of and skills in manipulating big data using SAS and open-source tools, using complex machine learning models, making business recommendations, and deploying models. Candidates must pass five exams to earn the SAS Certified Data Scientist credential.

SAS doesn’t require candidates to take certification courses as a prerequisite for exams, but the company offers an official curriculum for those who have the budget and need the extra preparation.

SAS “versioned” credentials, such as the SAS Certified Data Scientist Using SAS 9, do not expire. However, SAS may retire exams as new or enhanced software is released.

SAS Certified Data Scientist facts and figures

<td”>$180; Predictive Modeling test is $250

See the Certification Discount Packages webpage for discounts for faculty, staff, students, veterans and others.

</td”>

Beyond the top 5: More big data certifications

It was a real challenge to whittle down this year’s list of popular big data certifications. The Cloudera Certified Professional Data Engineer (CCP Data Engineer) missed a spot in the top five by a small margin. The company also offers CCA Spark and Hadoop Developer and CCA Data Analyst certifications. Given the company’s leadership status in software and services based on Hadoop, the CCP Data Engineer certification is worth your consideration.

Other notable certifications include the IBM Certified Data Architect, the EMC: Data Science (EMCDS), and those from Amazon Web Services (AWS), Hortonworks, MapR and Teradata.

Check out Stanford’s Data Mining and Applications graduate certificate. Although it’s not a vendor-neutral or vendor-specific certification (it’s a college certificate), TechExams forum members like it in terms of popularity and job prospects. The certificate requires completion of three courses (nine college units) at a cost of $11,340 to $12,600. The Microsoft Professional Program (MPP) currently offers four tracks for online education with course completion certificates, including two relevant tracks: one on data science, the other on big data. These are worth checking out as well, and significantly cheaper than the Stanford certificate program.

There are many more. A quick Google search every month or two should reveal a growing list of big data, data analytics and BI certifications, and we think one or more of these is a smart way to spend your certification dollars.

The MarketWatch News Department was not involved in the creation of this content.

Feb 08, 2023 (The Expresswire) -- Open-Source Database Software Market Size 2023-2029 | New Report (111 Pages) | In This Reports Open-Source Database Software Market and its business scene, significant issues, answers for relieving the upgrading risk, methodologies, future lookout, and possibilities, Other than the standard design reports, Top Open-Source Database Software Companies (MySQL, MariaDB, Titan, Neo4j, Redis, SQLite, MongoDB, Couchbase, Apache Hive) with the best facts and figures, definitions, SWOT and PESTAL analysis, expert opinions and the latest trends around the world.

The MarketWatch News Department was not involved in the creation of this content.

Role-specific knowledge:

• At least 3-5+ years of experience in executing data solutions using MongoDB.
• Configuring schema and MongoDB data modeling
• Experience with database security management
• Experience with MongoDB Atlas
• Thorough understanding of MongoDB architecture
• Java, Python, or TypeScript
• Git and CI/CD
• Web services / REST API
• Experience working in a SCRUM and DevOps environment.

Advantageous:

• AWS solution architecture experience
• AWS in general, Amazon Lambda, ECS, S3, SNS, SQS, DynamoDB, CloudWatch
• AWS CDK
• Amazon Glue, Athena
• Angular
• Jenkins
• Docker
• AGILE and/or SCRUM

Duties:

• Operate MongoDB Atlas cluster.
• Improve provisioning and monitoring of MongoDB Atlas cluster.
• Assess and Excellerate the MongoDB data model.
• Assess and Excellerate application usage of MongoDB.
• Plan for scaling, including sharding
• Prepare necessary documentation.
• Solve performance issues.
• Develop MongoDB and API prototypes and proofs of concept.
• Automate routine DB operations with scripting.

Minimum Requirements:

Formal qualifications:

• Computer science, engineering, or mathematics degree, or equivalent proven experience
• Several years of experience building solutions using Mongo DB
• Several years of experience using Java, Python, or TypeScript

Desired Skills:

• MongoDB
• Java
• Python
• aws
• Atlas Cluster

Learn more/Apply for this position

All digital modernisation initiatives depend on enabling software developers to write great software applications. Traditionally, software developers have spent a huge amount of time wrestling with data, working around the limitations of legacy systems. Organisations need to enable software developers to build quickly and efficiently by removing the friction, especially in a climate of economic uncertainty where agility and cost efficiency are top of mind.

With MongoDB Atlas, a developer data platform, enterprises can enable their software developers to operate with speed and agility while putting data at the core of their business even when they find resources and budget getting tighter. 

Computing spoke with Andrew Davidson, SVP of Products at MongoDB, to learn about democratising the ability to build ‘smart' apps and the exciting developments that occur as a result.

Why should businesses be opting for NoSQL (document model) database programs like MongoDB's, instead of traditional ones?

"We're in the very early stages of a long-term secular shift. When you think about the relational, table-based data model that came out of the 1970s, the model was anchored to the key cost bottleneck of the time - storage costs. Today, storage and infrastructure building blocks are no longer bottlenecks. Instead, the key cost obstacle is developers' minds.

"We need to be empowering developers as the artisans of our new digital economy. Organisations must supply developers the right open and composable abstractions to build with.

"MongoDB's document data model gives developers a native, idiomatic way of interacting with data that for the first time doesn't force them to transform their data into tables. Our platform gives them the freedom of having a flexible model, enabling coding in the way they already think at the data layer. We've coupled that with being a distributed system early on, synergistically with the rise of cloud."

What have been the main data challenges for organisations in the past few years?

"The key data challenge is how to build software and applications effectively but quickly and achieve this where data is born and where it can be put to use. Operational data challenges often get lost in this debate - where software developers are toiling every day. These challenges hold back the ability for people to build applications and generate interesting new experiences. Unlocking the data where it's born is how to start building interesting business value.

"There's an enormous amount of management overhead that can go into traditional data systems that need to be augmented by key value systems, search engines, and caches, each requiring its own interfaces for developers with its own operational best security or patching practice.

"To be able to flip that on its head and have one declarative model managed with modern operational paradigms to supply the builder (application developers) exactly what they want - transactional capabilities, search capabilities, application-driven analytics capabilities, device synchronisation capabilities - enables teams to move faster with autonomy and self-service agility."

How will ‘smart' apps, with embedded intelligence, be a gamechanger? Where does MongoDB fit in?

"There are classic examples - using the embedded intelligence in an industrial supply chain or manufacturing context to predict a machine failing or maintenance needs. Or with fraud analytic scenarios that need real-time payment determinations of what is real vs fraudulent. When it comes to application-driven analytics, it involves not just human visibility of insights, but being able to have software on top of software to make decisions and take actions.

"Personally, I'm excited about how MongoDB will be employed in a way we don't yet know because we're making things so much more accessible, democratising access to powerful building blocks for builders. Just as technology shifted with the rise of mobile or cloud and possibilities were consequently opened up in  ways no one could have predicted These building blocks will enable meaningful changes to all our lives. I'm particularly excited about the power of Atlas Search, search will be the ubiquitous front door into so many applications, and it will power so many of the experiences we know and love (think auto-complete, faceting and more). For teams that don't have dedicated specialist teams, building with search natively out of the box in their database is a game changer that will enrich so many of the smart applications we'll all use.

What are the benefits to democratising access to data and analytics?

"Increasingly we're in a software-defined economy, meaning software developers are critical to every kind of business. Organisations can struggle to make developers effective or productive, not to mention they are expensive, hard to retain and difficult to hire. Giving developers a data model aligned to where they write their code, and the objects in their code can go directly to the database, means they can move much faster. There's no need to bolt on a different engine, database, or data system for each feature and each different application."

"Smart, intelligent applications are easier to build by more and more people. MongoDB Atlas gets 150,000 people signing up every month. There's a stadium full of people every month wanting to use a developer data platform. There are people coming up with a new idea that we've never thought of before. There's going to be so many more things that will enhance our lives in ways we're not thinking about yet.

"The number of developers is on the rise and it's interesting to watch more traditional enterprises and governments see this growing dynamic and strive to get a step ahead to avoid disruption. There's going to be empowerment of the citizen developer."

What should organisations be prioritising for investment in the new year amid economic uncertainty?

"Across industries we're facing a time of increased investment scrutiny. Leaders right now are focused on reducing cash burn as well as prioritising what matters most for their company and its future. Organisations need to be investing in adopting technologies that allow them to do more with resources in an agile way. I think it's a question of modernising where appropriate onto platforms that allow sophistication and agility - but be prudent about it.

"The ability for software engineers to build software applications that express the critical internal business processes, external customer-facing experiences, and internal employee experiences are the lifeblood of these companies. Today, all industries run software on top of software with layers of microservices largely invisible to us. People tasked with building all of this are the lubrication of the digital economy - they need to be able to do an enormous amount with less. With expectations to move faster, or if your competitors are raising the bar and you're not - you're being left behind."

To find out more about MongoDB visit mongodb.com

This post was funded by MongoDB.

Role-specific knowledge:

• At least 3-5+ years of experience in executing data solutions using MongoDB.
• Configuring schema and MongoDB data modeling
• Experience with database security management
• Experience with MongoDB Atlas
• Thorough understanding of MongoDB architecture
• Java, Python, or TypeScript
• Git and CI/CD
• Web services / REST API
• Experience working in a SCRUM and DevOps environment.

Advantageous:

• AWS solution architecture experience
• AWS in general, Amazon Lambda, ECS, S3, SNS, SQS, DynamoDB, CloudWatch
• AWS CDK
• Amazon Glue, Athena
• Angular
• Jenkins
• Docker
• AGILE and/or SCRUM

Duties:

• Operate MongoDB Atlas cluster.
• Improve provisioning and monitoring of MongoDB Atlas cluster.
• Assess and Excellerate the MongoDB data model.
• Assess and Excellerate application usage of MongoDB.
• Plan for scaling, including sharding
• Prepare necessary documentation.
• Solve performance issues.
• Develop MongoDB and API prototypes and proofs of concept.
• Automate routine DB operations with scripting.

Minimum Requirements:

Formal qualifications:

• Computer science, engineering, or mathematics degree, or equivalent proven experience
• Several years of experience building solutions using Mongo DB
• Several years of experience using Java, Python, or TypeScript

Desired Skills:

• MongoDB
• Java
• Python
• aws
• Atlas Cluster

Learn more/Apply for this position

Credit: Supplied

2023 promises to be a vital year for MongoDB in New Zealand as the company aims to capitalise on the launch of local hyperscale cloud facilities.

A/NZ country manager Anoop Dhankhar told Reseller News the fast growing company, which hit US$1 billion in revenue earlier this year, already had partners on the ground locally as it also wooed local customers through the three major hyperscale cloud providers: Google Cloud Platform (GCP), AWS and Microsoft Azure.

In a sign of that intent, MongoDB hosted an event in Auckland in November where it presented a business growth update and insights from key local customer Lumin, a Christchurch-based developer of electronic document technology.

While MongoDB's heritage is as an open source provider of database technology, since 2017 it has styled itself as the provider of a SaaS data platform for systems integrators and developers who need to build high-performance distributed applications quickly and at scale.

That platform, dubbed Atlas, is now where most of MongoDB's revenue comes from.